Triglyceride Glucose-Waist Circumference Is Superior to Other Biochemical Indicators for Diagnosing Prehypertension and Hypertension
Bibliographic record
Abstract
Background: In situations with economic issues and limited resources, prevention and early detection of hypertension are essential for its control. Diagnosis and treatment require considerable expenses, which could lead to an incomplete diagnosis and, therefore, a higher prevalence. The aim of this study was to evaluate the usefulness of eight biochemical indices as diagnostic tools for prehypertension and hypertension. Methods: This is a diagnostic testing study. The variables were hypertension and prehypertension. Among the markers evaluated were triglycerides/high-density lipoprotein cholesterol (HDL-C), cholesterol/HDL-C, low-density lipoprotein (LDL)/HDL-C, visceral adiposity index, lipid accumulation product, the triglyceride-glucose (TyG) index, TyG-waist circumference (TyG-WC), and TyG-body mass index (TyG-BMI). The receiver operating characteristic (ROC) curve analysis was used as a statistical and graphical method to evaluate diagnostic capacity, as well as the area under the curve (AUC) corresponding to each response variable. Sensitivity (Se) and specificity (Sp) were calculated, along with their 95% confidence intervals (95% CIs). Results: The prevalence of undiagnosed prehypertension and hypertension was 6.88% and 2.72%, respectively. The TyG-WC has been the best indicator for both prehypertension: AUC = 0.712 (95% CI: 0.650 - 0.775), cutoff = 762.56, Se = 90.74 (95% CI: 79.70 - 96.92), and Sp = 45.24 (95% CI: 41.61 - 48.92), in terms of diagnostic capacity. The same applies to hypertension: AUC = 0.801 (95% CI: 0.718 - 0.883), cutoff = 862.57, Se = 81.81 (95% CI: 59.72 - 94.81), and Sp = 70.18 (95% CI: 66.84 - 73.35). Conclusions: The TyG-WC is the best diagnostic tool for prehypertension and hypertension; hence, it is necessary to conduct prospective research to verify these findings. If confirmed, the TyG-WC can be used as a marker for the prognosis of these two conditions and, thus, to make decisions about prevention. J Endocrinol Metab. 2023;13(4):135-143 doi: https://doi.org/10.14740/jem886
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".